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    <title>sskf</title>
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    <center>Scilab Function</center>
    <div align="right">Last update : April 1993</div>
    <p>
      <b>sskf</b> -  steady-state Kalman filter</p>
    <h3>
      <font color="blue">Calling Sequence</font>
    </h3>
    <dl>
      <dd>
        <tt>[xe,pe]=sskf(y,f,h,q,r,x0)  </tt>
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    <h3>
      <font color="blue">Parameters</font>
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    <ul>
      <li>
        <tt>
          <b>y</b>
        </tt>: data in form <tt>
          <b>[y0,y1,...,yn]</b>
        </tt>, <tt>
          <b>yk</b>
        </tt> a column vector</li>
      <li>
        <tt>
          <b>f</b>
        </tt>: system matrix dim(NxN)</li>
      <li>
        <tt>
          <b>h</b>
        </tt>: observations matrix dim(MxN)</li>
      <li>
        <tt>
          <b>q</b>
        </tt>: dynamics noise matrix dim(NxN)</li>
      <li>
        <tt>
          <b>r</b>
        </tt>: observations noise matrix dim(MxM)</li>
      <li>
        <tt>
          <b>x0</b>
        </tt>: initial state estimate</li>
      <li>
        <tt>
          <b>xe</b>
        </tt>: estimated state</li>
      <li>
        <tt>
          <b>pe</b>
        </tt>: steady-state error covariance</li>
    </ul>
    <h3>
      <font color="blue">Description</font>
    </h3>
    <p>
    steady-state Kalman filter</p>
    <h3>
      <font color="blue">Author</font>
    </h3>
    <p>C. B.  </p>
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